A business enterprise may rely on data warehouses and computing services to store and process data that facilitate daily operations. The data warehouses may reside on various servers, each potentially having different characteristics and capabilities. During operations, entities within the business enterprise may use the computing services and the data stored in the data warehouses to complete different tasks. For example, a computing task may be a creation of a data report, such as a financial report, a sales projection report, or an inventory information report. However, in some instances, the ability of an entity to complete the computing task may be constrained by the entity's dependency on data that is generated and placed into the data warehouses by other entities. The ability of the entities to complete their respective tasks may be further constrained by the processing capability of the servers that host the database warehouses and the computing services, as well as the computing task workload that is placed on the servers by the various entities. Additionally, different entities may request different task completion times, which may add another layer of complexity to the scheduling of computing tasks for execution.
Thus, in scenarios in which the data stored in the data warehouses and the computing services are used by multiple entities to complete a significant number of tasks, the prioritization of such tasks for execution may become increasingly complex. Accordingly, as the number of tasks increases, it may become infeasible for a human operator to make decisions regarding the order in which the computing tasks are to be efficiently executed.